Spread of Influence in Weighted Networks under Time and Budget Constraints

TL;DR

This paper studies influence spread in weighted networks under time and budget constraints, proving NP-hardness and providing efficient algorithms for special cases like trees, paths, cycles, and complete graphs.

Contribution

It introduces the first pseudo-polynomial algorithms for influence spread in general trees and improves existing algorithms for unweighted trees.

Findings

NP-hardness proven even in simple networks

Pseudo-polynomial algorithms for general trees

Polynomial algorithms for paths, cycles, and complete graphs

Abstract

Given a network represented by a weighted directed graph G, we consider the problem of finding a bounded cost set of nodes S such that the influence spreading from S in G, within a given time bound, is as large as possible. The dynamic that governs the spread of influence is the following: initially only elements in S are influenced; subsequently at each round, the set of influenced elements is augmented by all nodes in the network that have a sufficiently large number of already influenced neighbors. We prove that the problem is NP-hard, even in simple networks like complete graphs and trees. We also derive a series of positive results. We present exact pseudo-polynomial time algorithms for general trees, that become polynomial time in case the trees are unweighted. This last result improves on previously published results. We also design polynomial time algorithms for general weighted paths and cycles, and for unweighted complete graphs.